"Students will be expected to develop fair test procedures, [create meaningful data displays, make reasonable and data supported reports, and analyze their collected data in light of the problem at hand]."
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the "fair test" is to be applied by the students, not on the students; the fairness expected is not in relation to the students but in relation to the results expected from the activity.

It's this kind of "fair tests":

"Fair tests: A do-it-yourself guide

Which brand of chocolate chip makes the best tasting cookies? Is the tree outside your window causing your runny nose? Why won't your car start? If you want to answer questions like these, you'll probably need to do some testing.

But all tests are not created equal. In order to figure out the real answers to such questions, you'll need to test your ideas in a fair way.

Chocolate chip cookies, car trouble, allergic reaction

Testing can help you pick the tastiest brand of chocolate chip, figure out why you're sneezing, or find out why your car won't start.

The considerations that go into making "everyday" tests fair are the same ones that scientists consider when they test their ideas using experiments and other methods. Whether one wants to optimize a chocolate chip cookie recipe, develop effective treatments for Alzheimer disease, learn more about how mass extinctions work, or investigate the workings of gravity, the components of a fair test are the same:

Comparing outcomes. ...

Controlling variables. ...

Avoiding bias. ...

Distinguishing chance from real differences. ...

DETECTING THE DIFFERENCES: STATISTICS AND SAMPLE SIZE
You might be wondering, what counts as a "large" sample size? Twenty, 200, or 2000 chocolate chip cookies?
...
It is often impossible to make a test perfectly fair, and each issue listed above may be more or less important for a particular test — but by considering each of these factors in how your test is designed, you can maximize the amount of useful information you get from the test.

Above, we gave an example of testing in everyday life, but the same set of considerations can be applied to tests in more traditionally scientific realms — and to tests that don't involve experiments. To see real-life examples of fair test design in science, follow the links below:

Fair tests in the field of medicine: Aiding Alzheimer patients

Fair tests in the fossil record: Avoiding extinction

Fair tests in physics: Examining eclipses
[http://undsci.berkeley.edu/article/fair_tests_01]



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Note added at 1 day4 hrs (2014-02-12 14:47:23 GMT) Post-grading
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correction:

procédures d'essai objectives